import org.apache.spark.graphx.{Edge, Graph, VertexId}
import org.apache.spark.rdd.RDD
import org.apache.spark.{SparkConf, SparkContext}

object FirstGraphX {

  def main(args: Array[String]): Unit = {

    //设置运行环境
    val conf = new SparkConf().setAppName("FirstGraphX").setMaster("local")
    val sc = new SparkContext(conf)
    sc.setLogLevel("WARN")

    //设置users顶点
    val users: RDD[(VertexId, (String, Int))] =
      sc.parallelize(Array(
        (1L, ("Alice", 28)),
        (2L, ("Bob", 27)),
        (3L, ("Charlie", 65)),
        (4L, ("David", 42)),
        (5L, ("Ed", 55)),
        (6L, ("Fran", 50))))

    //设置relationships边
    val relationships: RDD[Edge[Int]] =
      sc.parallelize(Array(Edge(2L, 1L, 7), Edge(2L, 4L, 2), Edge(3L, 2L, 4), Edge(3L, 6L, 3),Edge(4L, 1L, 1),Edge(5L, 2L, 2),Edge(5L, 3L, 8),Edge(5L, 6L, 3)))


    // Build the initial Graph
    val graph = Graph(users, relationships)

    println("---------------------------------------------")


    println("找出图中年龄大于 30 的顶点")
    graph.vertices.filter { case (id, (name, age)) => age >= 30 }.collect.foreach {
      case (id, (name, age)) => println(s"$name is $age")
    }

    println("---------------------------------------------")
    println("找出图中属性大于 5 的边")
    graph.edges.filter(e => e.attr >= 5).collect.foreach(e => println(s"${e.srcId} to ${e.dstId} att ${e.attr}"))

    println("---------------------------------------------")
    println("找出图中最大的出度、入度、度数：")
    def max(a: (VertexId, Int), b: (VertexId, Int)): (VertexId, Int) = {
      if (a._2 > b._2) a else b
    }

    println("max of outDegrees:" + graph.outDegrees.reduce(max) + " max of inDegrees:" + graph.inDegrees.reduce(max) + " max of Degrees:" + graph.degrees.reduce(max))
  }

}